import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class 	_lowerCAmelCase		(  lowerCamelCase__   , lowerCamelCase__   , lowerCamelCase__					):







							@register_to_config
							def __init__(					self  :     int						,       __snake_case  :     int						,       __snake_case  :     int						,       __snake_case  :     int						,       __snake_case  :     float						,       __snake_case  :     int						,       __snake_case  :     int						,       __snake_case  :     int						,       __snake_case  :     int						,       __snake_case  :     str						,       __snake_case  :     bool = False						,       ):
										super().__init__()

										lowerCamelCase    :Tuple    	=  nn.Embedding(__snake_case						,       __snake_case		)

										lowerCamelCase    :Dict    	=  nn.Embedding(__snake_case						,       __snake_case		)
										lowerCamelCase    :Tuple    	=  False

										lowerCamelCase    :Optional[Any]    	=  nn.Dropout(p=__snake_case		)

										lowerCamelCase    :int    	=  TaConfig(
										    vocab_size=__snake_case						,       d_model=__snake_case						,       num_heads=__snake_case						,       d_kv=__snake_case						,       d_ff=__snake_case						,       dropout_rate=__snake_case						,       feed_forward_proj=__snake_case						,       is_decoder=__snake_case						,       is_encoder_decoder=__snake_case						,       )

										lowerCamelCase    :Optional[int]    	=  nn.ModuleList()
										for lyr_num in range(__snake_case		):
													lowerCamelCase    :List[Any]    	=  TaBlock(__snake_case		)
													self.encoders.append(__snake_case		)

										lowerCamelCase    :int    	=  TaLayerNorm(__snake_case		)
										lowerCamelCase    :Tuple    	=  nn.Dropout(p=__snake_case		)







							def 					snake_case	(					self  :     Optional[Any]						,       __snake_case  :     Tuple						,       __snake_case  :     str		):
										lowerCamelCase    :Optional[Any]    	=  self.token_embedder(__snake_case		)

										lowerCamelCase    :List[Any]    	=  encoder_input_tokens.shape[1]
										lowerCamelCase    :Tuple    	=  torch.arange(__snake_case						,       device=encoder_input_tokens.device		)
										x += self.position_encoding(__snake_case		)

										lowerCamelCase    :Optional[Any]    	=  self.dropout_pre(__snake_case		)

										# inverted the attention mask
										lowerCamelCase    :Optional[int]    	=  encoder_input_tokens.size()
										lowerCamelCase    :Optional[int]    	=  self.get_extended_attention_mask(__snake_case						,       __snake_case		)

										for lyr in self.encoders:
													lowerCamelCase    :Any    	=  lyr(__snake_case						,       __snake_case		)[0]
										lowerCamelCase    :Optional[Any]    	=  self.layer_norm(__snake_case		)

										return self.dropout_post(__snake_case		), encoder_inputs_mask








'''simple docstring'''






def  lowerCamelCase__			(		_A					,     _A					,     _A=False							):

  if isinstance(_A					,     _A							) and isinstance(_A					,     _A							):
    a		:   Tuple	  =	len(set_a.intersection(_A							)							)

    if alternative_union:
      a		:   Union[str, Any]	  =	len(_A							) + len(_A							)
    else:
      a		:   Optional[Any]	  =	len(set_a.union(_A							)							)

    return intersection / union

  if isinstance(_A					,     (list, tuple)							) and isinstance(_A					,     (list, tuple)							):
    a		:   int	  =	[element for element in set_a if element in set_b]

    if alternative_union:
      a		:   Optional[int]	  =	len(_A							) + len(_A							)
      return len(_A							) / union
    else:
      a		:   Tuple	  =	set_a + [element for element in set_b if element not in set_a]
      return len(_A							) / len(_A							)

    return len(_A							) / len(_A							)
  return None


if __name__ == "__main__":
     lowerCAmelCase:   str					=		{'a', 'b', 'c', 'd', 'e'}
     lowerCAmelCase:   Optional[Any]					=		{'c', 'd', 'e', 'f', 'h', 'i'}
     print(jaccard_similarity(set_a, set_b))